This invention pertains to a computational architecture structure, and more particularly to a structure which is based on neural-model connectionism.
Recently, the use of the so-called "connectionist" model has gained popularity as an alternative computational paradigm for artificial intelligence systems that display cognitive behavior. Connectionist models are based on the structure of the brain's neural networks, and because of this, are capable of exhibiting computational behavior which is similar to that of the brain. The most important part of such behavior is the ability to process an input and to reach a conclusion in a few steps, instead of the usual thousands of steps which take place in a typical, sequential computer program.
Connectionist models consist of many simple processors that modify the strengths of their interconnections in order to store data. These processing elements in a connectionist network do not solve a given problem individually. Instead, they compute by being connected appropriately to large numbers of similar units. More specifically, they function by generating, in parallel, multiple competing hypotheses, and by then relaxing to a single, best-match interpretation.
In the system disclosed herein, two types of processors are involved. One of these is referred to as a connection node which is a virtual element rather than a physical element. A connection node performs as a simple computing "center". The particular function that is computed by a connection node is dependent on the particular connectionist model that has been selected. Implementation of the present invention is in no way dependent upon this selected function, and accordingly, no function discussion is included in the text which follows.
The other kind of processor is referred to as a physical node, which is a physical element. A physical node takes the form of an independent processor which is capable of performing standard arithmetic and logical computations.
Directly associated with each physical node are plural connection nodes. Stated more precisely, each physical node "creates" its associated connection nodes through using data stored within a memory structure which also forms part of the physical node.
In a prior-filed patent application covering an invention by us, filed Feb. 24, 1987 Ser. No. 017,788 for NEURAL-MODEL, INFORMATION-HANDLING ARCHITECTURE AND METHOD, where a broadcast-hierarchical, neural-model connectionist architecture structure and method are disclosed. This particular architecture structure has special utility in circumstances where a correct assumption exists that long connections are used for communication less frequently than short connections. In such a setting, characterizable as "temporal locality", the structure there described most efficiently handles computational activity.
In other kinds of situations where substantially all connections are used very frequently with few long connections made, "spatial locality", another kind of architecture structure is best suited to maximize computational efficiency.
A principal object of the present invention is to provide a unique architecture structure which deals with the "spatial locality" type situation just mentioned and which organizes and employs physical nodes and connection nodes in a manner that tends to maximize certain capabilities and advantages of a neural-model, connectionist, computational network.
According to a preferred embodiment of the invention, what is proposed herein is an organization which is characterized by plural, layered groups of connection nodes collected in what are referred to herein as broadcast regions. These broadcast regions overlap in a rearward and backward sense, and also in a lateral sense. The broadcast regions are, in fact, defined by broadcast bus structures which are specific to their respective associated regions.
This kind of an organization, unique in the field of neural-model connectionist architecture, offers, for a given physical territory and number of connection nodes, a vast number of communication (connection) possibilities in a very short span of time.